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Education in Emergencies (EiE) Data Tip Sheets: Finding and Using Data for EiE

Published on:

May 1, 2020

By:

Middle East Education Research Training and Support (MEERS) initiative

Author

Social Impact and FHI360

Organization

USAID

Institution

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Insights from the Education in Emergencies (EiE) field are more relevant than ever, as the world collectively confronts the educational effects of a global pandemic. The mitigation policies necessary to protect our health from COVID-19 have resulted in school closures in more than 180 countries, with more than 1.5 billion students out of school at the end of March 2020. In these uncertain times, it is important to reflect on how existing data can be used to inform EiE work.

There is a common and persistent myth that there is no data relevant to education in emergencies. Although data gaps exist, there are many sources of data that can be used to inform EiE work. For example, humanitarian education data from national education clusters can be used to inform who is doing what, where, and when in a specific emergency context. Additionally, forced displacement data from UNCHR or IOM’s Displacement Tracking Matrix can provide critical information on the location and movement of affected populations. Unfortunately, these data sources are not used as often as they could be.

FHI 360 has developed a series of EiE Data Tip Sheets to help the expanding EIE community use existing data to inform their work. The three tip sheets provide guidance to identify the primary purpose that data are needed for, where to find relevant data, and how to interpret the data.

Tip Sheet #1: How to USE EiE Data presents a Data Use Framework that was developed through research and discussions with experts in the field. This is presented first to encourage practitioners to first determine specific data needs and the population involved to ensure that data are fit-to-purpose, and then search for and act upon collected data. Identifying the data use and users will also help you more efficiently navigate the broad array of data sources in the second tip sheet. For example, an EiE program staff in Yemen may identify a need to use data for coordination with other education programs operating in the same locality. Once the program staff identifies the use and users of the data using Tip Sheet #1, they can then turn to Tip Sheet #2 to navigate potential data sources.

Tip Sheet #2: How to FIND EiE Data organizes the many data sources available by category: humanitarian operations, educational development, or population movements and context. The data sources are also organized based on how frequently data are updated and whether they provide raw data or user-friendly data exploration tools to help you tailor the data source to the needs of your data use and users. To continue the example from above, the EiE program staff may identify a need for localized and frequent data to inform coordination. Using Tip Sheet #2, they would find that humanitarian operations data from sources such as Humanitarian Response and ReliefWeb may have data from humanitarian education dashboards that inform coordination. Once they find potential EiE data sources, the next step is to interpret and analyze the data to optimize its usefulness for specific audiences.

Tip Sheet #3: How to INTERPRET EiE Data provides broad guidance to consider when interpreting and analyzing data. The first part of the tip sheet presents suggestions about how to assess the relevance and reliability of the data for your purposes. The final portion suggests how to disaggregate data and how to use various types of comparison to enhance the meaningfulness of the data for your users. To return to our example, the EiE program staff can use Tip Sheet #3 to check the temporality, geography, and quality of the coordination data source to ensure that it is updated frequently enough and disaggregated by location.

We hope that these tips sheets will help the large and growing EiE community to more effectively and efficiently use data for decision making. We encourage our colleagues and the community to make use of existing data where possible, to focus new data collection on filling critical gaps, and to ensure that data inform actions to support teachers and students around the globe.

These tip sheets were developed by Annie Smiley (FHI360), Sean Cremin (FHI360), Daniel Shephard (Teachers College, Columbia University), Tanya Smith-Sreen (FHI360), and Elizabeth Buckner (University of Toronto) through the USAID-funded Middle East Education Research Training and Support (MEERS) initiative.

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